Abstract: Adaptive dictionary learning algorithms jointly optimize sparse representations and dictionary atoms to enhance performance. However, this alternating minimization process is complex, and ...
Figure 1. Relationship between artificial intelligence (AI), machine learning (ML), deep learning (DL), and data science and basic definitions. Figure 2. Representation of the Rosalind Franklin ...
Taking a sparse user-supplied MIP solution, fixing the corresponding variables, and solving the resulting MIP to optimality may be very expensive, and not worth the investment. Introduce a "light" ...
Robotic racket sports provide exceptional benchmarks for evaluating dynamic motion control capabilities in robots. Due to the highly non-linear dynamics of the shuttlecock, the stringent demands on ...
Anton Osika is the CEO of Lovable AI, a vibe coding platform that enables users to build apps from text prompts. Osika said in a new interview that traits like curiosity and adaptability are more ...
As companies like Amazon and Microsoft lay off workers and embrace A.I. coding tools, computer science graduates say they’re struggling to land tech jobs. Manasi Mishra recently graduated from Purdue ...
STG-DMD (Sparse-Coded Time-Delay Graph Dynamic Mode Decomposition) is a data-driven framework for modeling nonlinear dynamics on graph structures. It integrates: StgDmd/ ├── code/ │ ├── artificial/ │ ...
As someone who chats with startup founders for a living, I've always admired the "builders." I have a lot of respect for their technical ability to dream up an idea and code it into existence, but ...
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